Visualization of the Week: Evaluating basketball teams as networks

Had the Lakers consulted with Arizona State University (ASU) researchers Jennifer Fewell and Dieter Armbruster, they might have gone a different way after firing coach Mike Brown. Nonetheless, current Lakers coach Mike D’Antoni may be wise to consult Fewell and Armbruster’s work. The duo led a team at ASU that used a network analysis model to analyze basketball plays — they applied the technique to the 2010 NBA playoffs to help explain the results.

According to their published research paper, “[t]he study involved more than a thousand ball movements and typically more than one hundred sequences or paths for each team” in the playoffs, which provided enough data to enable them to treat the game as a network.

“Weighted graphs of ball transitions across two games for the (d) Lakers. Red edges represent transition probabilities summing to the 60th percentile. Player nodes are sorted by decreasing degree clockwise from the left.”

The team explains in their paper how they were able to execute a network analysis on the game:

“To evaluate basketball teams as networks, we examined the offensive ball sequences by National Basketball Association (NBA) teams during the first round of the 2010 playoffs. We graphed player positions and inbound/outcomes as nodes, and ball movement among nodes (including shots to the basket) as edges. From the iterated offensive 24 second clocks, we recorded sequences of ball movement of each of the 16 play-off teams across two games. … We were interested in whether network metrics can usefully quantify team decisions about how to most effectively coordinate players. We examined two network metrics that we hypothesized might capture different offensive strategies. One is to move the ball in a way that is unpredictable and thus less defensible. … Another, not mutually exclusive, strategy is to capitalize on individual expertise by moving the ball towards players with high probability of shooting success.”

Brian Mossop at Wired highlighted a few conclusions from the team’s research. Notably, that the common practice of inbounding the ball to the point guard (something most teams followed during the 2010 playoffs) failed to produce reliable results. “On the other hand,” writes Mossop, “the Los Angeles Lakers — which won the 2010 NBA championship — distributed the ball more evenly than their rivals, embracing what [then coach] Phil Jackson calls the ‘triangle offense,'” in which players are spaced out around the court, opening up passing options. Mossop notes the research team’s science behind the Laker’s success:

“In their model, Fewell and Armbruster found a mathematical explanation for why the triangle offense works — the point guard was no longer the only player feeding passes to fellow players; his teammates were just as likely to take on that role. With more potential passers, there are more potential paths for the opposition to defend.

Applications of this analysis model already are being employed, Mossop reports. Krossover Intelligence, for instance, is applying the analysis model to video playback in hopes of revolutionizing game tape analysis. “All of Krossover’s videos are searchable,” writes Mossop, “and their technology is sophisticated enough to create computer visualizations showing what players did — and, better yet, what they should have done.”

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